Rural‐Urban Disparities in Total Physical Activity, Body Composition, and Related Health Indicators: An Atlantic PATH Study
Bibliographic record
Abstract
PURPOSE: To describe and compare the sociodemographic and lifestyle characteristics of urban and rural residents in Atlantic Canada. METHODS: Cross-sectional analyses of baseline data from the Atlantic Partnership for Tomorrow's Health cohort were conducted. Specifically, 17,054 adults (35-69 years) who provided sociodemographic characteristics, measures of obesity, and a record of chronic disease and health behaviors were included in the analyses. Multiple linear regression and logistic regression models were used to calculate the multivariable-adjusted beta coefficients (β), odds ratios (OR), and related 95% confidence intervals (CI). FINDINGS: After adjusting for age, sex, and province, when compared to urban participants, rural residents were significantly more likely to: be classified as very active (OR: 1.19, CI: 1.11-1.27), be obese (OR: 1.13, 1.05-1.21), to present with abdominal obesity (OR: 1.08, CI: 1.01-1.15), and have a higher body fat percentage (β: 0.40, CI: 0.12-0.68) and fat mass index (β: 0.32, CI: 0.19-0.46). Rural residents were significantly less likely to be regular or habitual drinkers (OR: 0.83, CI: 0.78-0.89). Significant differences remained after further adjustment for confounding sociodemographic, lifestyle, and health characteristics. No significant differences in smoking behavior, fruit and vegetable intake, multimorbidity, or waist circumference were found. CONCLUSIONS: As expected, obesity prevalence was higher in rural Atlantic Canadians. In contrast to much of the existing literature, we found that rural participants were more likely to report higher levels of total physical activity and lower alcohol consumption. Findings suggest that novel obesity prevention strategies may be needed for rural populations.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".